A CRISP-DM-Based Multi-objective Optimization of Building Wall Panels Using PSO and SA

The building sector accounts for a substantial share of global energy consumption, with a significant portion lost through external walls. This study, based on the CRISP-DM framework, proposes a multi-objective optimization model using Particle Swarm Optimization (PSO) and Simulated Annealing (SA) to enhance wall design. Three criteria, thermal resistance, total thickness, and weight, were optimized using a refined dataset of ۲۰۷ materials. Materials were pre-classified, and penalties were applied to ensure construction feasibility and material diversity. Among ۱۲۰ panel combinations, PSO showed better accuracy and convergence (mean thermal deviation: +۰.۱۳ m²·K/W), while SA favored lighter solutions with slightly higher thermal resistance (mean: +۰.۱۸ m²·K/W). PSO explored a broader material range, whereas SA produced more focused selections. PSO is thus recommended for accuracy-driven applications, with SA as a complementary tool for exploring innovative solutions.

کلیدواژه ها:

Building Energy Efficiency ، CRISP-DM methodology ، Particle Swarm Optimization (PSO) ، Simulated Annealing (SA)